Riverine pollution is an increasing threat to ecosystem integrity and economic development, thus a need for effective monitoring to guide the management of ecosystem health. Opportunely, aquatic macroinvertebrates have been proven to indicate the health status of the rivers. However, there is scanty information about their use in Rwanda. This study used macroinvertebrates to assess the water quality of the Nyabarongo and Akagera Rivers following the Tanzania River Scoring System (TARISS). The study was carried out between May 2023 and March 2024 and covered 13 sampling sites. Macroinvertebrates were collected using a kick sampling method while water samples were collected following standard methods for measuring water properties. Sites were clustered, and multivariate methods were used to assess dissimilarities in taxa distribution. Further, the Focal Principal Component Analysis (FPCA) was performed to assess the association of macroinvertebrates with water physico-chemical parameters. Collected macroinvertebrates belonged to 34 families dominated by Chironomidae, Baetidae, and Culicidae. The TARISS metrics (mean ± standard deviation) indicated a score of 44.53 (± 2.69), a taxa number of 11 (± 0.6), and an average scope per taxa (ASPT) of 4.07 (± 0.8). Dissolved oxygen had a significant positive influence on the distribution and abundance of the Libellulidae family. Conversely, dissolved oxygen and electric conductivity had a significant negative relationship with the Caenidae and Aeshnidae families, respectively. The low values of the TARISS metrics portend the poor water quality of the Nyabarongo and Akagera Rivers. Thus, management practices and regular biomonitoring are recommended to ensure that the ecosystem health of these rivers is maintained.
This study explores the development of a comprehensive techno-economic model of environmental degradation based on the ReCiPe2016 approach named Financial Developed ReCiPe (FDR). The FDR considers cause-and-effect pathways of environmental degradation by ocean acidification, floods, acid rain, malnutrition, forest destruction, and waste more than the ReCiPe2016 in the midpoint and the environmental properties in the endpoint by considering tourism potential and intergenerational benefits. This model quantifies environmental degradation by the functions of fate factors (FF), effect factors (EF), exposure factors (XF), and economic impacts. These functions are developed for added cause-and-effect pathways, and the results were verified based on real studies. The uncertainties are considered by Individualist, Hierarchist, and Egalitarian perspectives, and the Monte Carlo Simulation (MCS) method is used to estimate the uncertainty level of variables. The results indicate the acceptability of the findings for the 20–1000-year infinite time horizon is about 13–38% variation. The FDR reveals significant deviations in the Hierarchist perspective compared to the ReCiPe2016; non-cancer diseases due to stratospheric ozone depletion and malnutrition by global warming are increased by approximately 17% and 13%, respectively. Each hectare of forest destruction’s impact on global warming, tourism, and timber resources equates to annual emission of 86 tons of CO2, 426 tons of PM2.5, and 1540 tons of crude oil, respectively. The ocean acidification effects from CO2 emissions compared to SO2 and terrestrial acidification, contributing about 0.03% in the Hierarchist perspective. Finally, the FDR model bridges the existing gap in lifecycle impact assessment (LCIA) in energy-intensive industries such as petrochemical industries.